The new paradigm for building powerful tools is to design them for AI models. Instead of complex GUIs, developers should create simple, well-documented command-line interfaces (CLIs). Agents can easily understand and chain these CLIs together, exponentially increasing their capabilities far more effectively than trying to navigate a human-centric UI.

Generative AI primarily changes an app's user interface, but agentic AI can bypass UIs entirely to complete tasks. This makes transaction-fulfillment apps, which constitute a huge portion of the market, vulnerable to being replaced by agents that act directly on a user's behalf.

The Browser Company's vision shifted from optimizing tab management to seeing the browser as the ideal "personal intelligence layer." The browser itself is just the enabling technology; the real value comes from using its unique access to all user context (apps, queries, history) to power a miraculous AI assistant.

The next frontier for AI in development is a shift from interactive, user-prompted agents to autonomous "ambient agents" triggered by system events like server crashes. This transforms the developer's workbench from an editor into an orchestration and management cockpit for a team of agents.

In this software paradigm, user actions (like button clicks) trigger prompts to a core AI agent rather than executing pre-written code. The application's behavior is emergent and flexible, defined by the agent's capabilities, not rigid, hard-coded rules.

The 'agents vs. applications' debate is a false dichotomy. Future applications will be sophisticated, orchestrated systems that embed agentic capabilities. They will feature multiple LLMs, deterministic logic, and robust permission models, representing an evolution of software, not a replacement of it.

For many knowledge workers, the browser is their primary IDE. AI tools that operate as embedded extensions can leverage the real-time context of a webpage, combine it with a user's broader work data, and provide powerful, in-the-moment assistance without forcing a context switch.

A new software paradigm, "agent-native architecture," treats AI as a core component, not an add-on. This progresses in levels: the agent can do any UI action, trigger any backend code, and finally, perform any developer task like writing and deploying new code, enabling user-driven app customization.

Legacy systems like CRMs will lose their central role. A new, dynamic 'agent layer' will sit above them, interpreting user intent and executing tasks across multiple tools. This layer, which collapses the distance between intent and action, will become the primary place where work gets done.